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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: torgo_tiny_finetune_F04_frozen_encoder |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# torgo_tiny_finetune_F04_frozen_encoder |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2948 |
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- Wer: 46.1800 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
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| 0.7886 | 0.85 | 500 | 0.2527 | 38.2003 | |
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| 0.0987 | 1.69 | 1000 | 0.2771 | 51.7827 | |
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| 0.0695 | 2.54 | 1500 | 0.2463 | 38.6248 | |
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| 0.0479 | 3.39 | 2000 | 0.2699 | 26.8251 | |
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| 0.0314 | 4.24 | 2500 | 0.2857 | 23.2598 | |
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| 0.0239 | 5.08 | 3000 | 0.2698 | 23.6842 | |
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| 0.0173 | 5.93 | 3500 | 0.2771 | 25.2122 | |
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| 0.0122 | 6.78 | 4000 | 0.2733 | 26.7402 | |
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| 0.0099 | 7.63 | 4500 | 0.2812 | 26.5705 | |
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| 0.0091 | 8.47 | 5000 | 0.2773 | 23.4295 | |
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| 0.0077 | 9.32 | 5500 | 0.2839 | 30.5603 | |
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| 0.0057 | 10.17 | 6000 | 0.2722 | 23.7691 | |
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| 0.0043 | 11.02 | 6500 | 0.2959 | 34.3803 | |
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| 0.0028 | 11.86 | 7000 | 0.2783 | 33.0221 | |
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| 0.0026 | 12.71 | 7500 | 0.3000 | 32.7674 | |
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| 0.0025 | 13.56 | 8000 | 0.2865 | 32.6825 | |
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| 0.0022 | 14.41 | 8500 | 0.2946 | 38.8795 | |
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| 0.0014 | 15.25 | 9000 | 0.2858 | 38.3701 | |
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| 0.0012 | 16.1 | 9500 | 0.2953 | 63.8370 | |
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| 0.0006 | 16.95 | 10000 | 0.2928 | 42.9542 | |
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| 0.0004 | 17.8 | 10500 | 0.2910 | 43.7182 | |
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| 0.0004 | 18.64 | 11000 | 0.2947 | 44.8217 | |
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| 0.0002 | 19.49 | 11500 | 0.2948 | 46.1800 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.7 |
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- Tokenizers 0.13.3 |
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